# Foundry vs Replicate AI

Foundry는 월간 방문 1,296, 전월 대비 성장률 -52.7%, 가격 문의 가격 모델을 기록합니다. Replicate AI는 월간 방문 904,038, 성장률 -8.4%, 유료 가격 모델을 기록합니다.

| 지표 | [Foundry](https://openaitools.app/ko/tool/foundry) | [Replicate AI](https://openaitools.app/ko/tool/replicate-ai) |
| :--- | :--- | :--- |
| 웹사이트 URL | https://www.thefoundryai.com | https://replicate.com |
| 카테고리 | AI Agent, AI 개발자 도구, AI 테스팅 | AI API, AI 모델, AI 개발자 도구, 오픈소스 AI 모델 |
| 가격 모델 | 가격 문의 | 유료 |
| 월간 방문 수 | 1,296 | 904,038 |
| 전월 대비 성장률 | -52.7% | -8.4% |
| 주요 시장 | 미국 | 미국 |
| 직접 방문 | 506 | 577,501 |
| 리뷰 점수 | 4.3 | 4.6 |
| 저장 수 | 0 | 5 |
| 지원 플랫폼 | 웹사이트 | 웹사이트 |

## Foundry

Foundry is an enterprise simulation and data platform for teams building AI web agents, combining deterministic browser environments, structured agent evaluation, annotated datasets, and reinforcement learning at scale.

**가격 및 요금제:** Pricing is not published publicly. Foundry currently operates a gated private beta with an "Apply for Access" flow, and commercial terms are discussed directly with the team.

- **Deterministic browser simulation:** Pixel-perfect, reproducible browser environments that eliminate web drift, noise, and rate limits so agent runs are comparable over time.
- **Structured agent evaluation:** Every action is tracked, classified, and tagged — click failures, layout shifts, and misfires are surfaced rather than silently swallowed.
- **Expert-annotated datasets:** Human annotators build custom, long-horizon training data for supervised fine-tuning of browser agents on real enterprise platforms.
- **Unlimited RL trajectories:** Safely sample and evaluate large numbers of trajectories to train browser agents at scale, without running into anti-bot constraints.
- **Python SDK integration:** Plug Foundry into an existing agent workflow with an SDK that exposes task reset, CDP URL, final state, state mutations, and event logs.

**강점:** Purpose-built for browser/web agents rather than generic LLM evaluation; Reproducible environments remove a major source of confusing noise in agent benchmarks; Error classification is granular, helping teams attribute failures correctly; Combines simulation, data annotation, and RL in one platform instead of three vendors

**한계:** Access is limited to a private beta application, so onboarding is not self-serve; No public pricing, which makes budgeting hard before talking to sales

[Profile (Markdown)](https://openaitools.app/ko/tool/foundry.md)

## Replicate AI

Replicate is a cloud API for running, fine-tuning, and deploying machine learning models. Spin up open-source and hosted models — from image, video, and audio generation to speech synthesis, captioning, and LLM inference — with one line of code, or package your own model with Cog and put it behind a production-ready API.

**가격 및 요금제:** Paid, usage-based — you only pay for what you use. Most public models are billed by runtime at per-second hardware rates; some models are billed per input and output (for example, $0.04 per output image on Flux 1.1 Pro, $3.75 per million input tokens on DeepSeek R1). Published GPU hardware ranges from about $0.81/hr for a T4 up to roughly $43.92/hr for 8x H100. Private deployments bill for setup, idle, and active time on dedicated hardware, and you can start for free. Enterprise and volume discounts available.

- **Thousands of models behind one API:** Run image, video, audio, speech, and language models through a uniform API surface, with official models for FLUX, Nano Banana, Seedream, Grok Imagine, MiniMax, Wan, Seedance, and more.
- **One-line-of-code inference:** Set up a model in minutes and make an API call in Python, Node, or plain HTTP after authenticating with an API token.
- **Cog packaging and custom deployments:** Package your own model with Cog, an open-source tool for packaging machine learning models, and deploy it on dedicated hardware that scales up and down with demand.
- **Model fine-tuning:** Fine-tune models on your own data, including fast-booting fine-tunes that are billed only while actively processing requests rather than for idle time.
- **Published hardware and inference rates:** Transparent per-second hardware rates across CPU, T4, L40S, A100, H100, and H200 configurations, with committed-spend options for multi-GPU capacity.

**강점:** Very broad model catalog spanning image, video, audio, speech, and LLMs behind one consistent API; Usage-based billing with openly published per-second hardware and per-output model rates; Cog makes it straightforward to package and deploy your own private models; Automatic scaling handles traffic spikes without manual capacity planning

**한계:** Costs are consumption-based and can rise quickly with heavy traffic or always-on private deployments; Private models bill for idle and setup time, not just request processing, unless they are fast-booting fine-tunes; Long-running GPU models can queue on shared public capacity during peak periods; It is an infrastructure layer, so you still need your own prompts, pipelines, and application code

[Profile (Markdown)](https://openaitools.app/ko/tool/replicate-ai.md)

## 자주 묻는 질문

### Foundry과(와) Replicate AI의 월간 트래픽은 어떻게 비교되나요?

Foundry의 월간 방문 수는 1,296이고, Replicate AI는 904,038입니다. 트래픽 추정치는 제품 품질이 아니라 사용자 규모를 나타냅니다.

### 두 도구의 성장률은 어떻게 비교되나요?

Foundry의 전월 대비 성장률은 -52.7%이며, Replicate AI는 -8.4%입니다.

### 가격은 어떻게 비교되나요?

Foundry: 가격 문의. Pricing is not published publicly. Foundry currently operates a gated private beta with an "Apply for Access" flow, and commercial terms are discussed directly with the team. Replicate AI: 유료. Paid, usage-based — you only pay for what you use. Most public models are billed by runtime at per-second hardware rates; some models are billed per input and output (for example, $0.04 per output image on Flux 1.1 Pro, $3.75 per million input tokens on DeepSeek R1). Published GPU hardware ranges from about $0.81/hr for a T4 up to roughly $43.92/hr for 8x H100. Private deployments bill for setup, idle, and active time on dedicated hardware, and you can start for free. Enterprise and volume discounts available.

## 대안

| # | 도구 이름 | 월간 방문 수 | 전월 대비 성장률 | 가격 모델 | Summary | Profile (Markdown) |
| :--- | :--- | :--- | :--- | :--- | :--- | :--- |
| 1 | [OpenRouter](https://openaitools.app/ko/tool/openrouter-ai) | 19,941,437 | -6.2% | 유료 | 다양한 제공자에 걸쳐 텍스트 및 멀티모달 프롬프트를 라우팅하는 데 탁월하지만, Replicate의 전용 맞춤형 ML 배포 기능은 없습니다. | [.md](https://openaitools.app/ko/tool/openrouter-ai.md) |
| 2 | [Google Antigravity](https://openaitools.app/ko/tool/google-antigravity) | 16,054,109 | +8.1% | 무료+유료 | 에이전트 우선 시대를 위한 Google의 개발 플랫폼 | [.md](https://openaitools.app/ko/tool/google-antigravity.md) |
| 3 | [Apify](https://openaitools.app/ko/tool/apify) | 4,147,762 | +3.9% | 무료+유료, 가격 문의 | 수많은 즉시 사용 스크레이퍼와 AI 에이전트를 한 클라우드에서 실행 | [.md](https://openaitools.app/ko/tool/apify.md) |
| 4 | [fal.ai](https://openaitools.app/ko/tool/fal-ai) | 3,093,684 | -3.7% | Paid, pay-as-you-go usage-based pricing | 이미지 및 비디오 모델을 위한 더 빠른 서버리스 실행을 제공하지만, Replicate에 비해 일반화된 커스텀 모델 배포 기능은 다소 적습니다. | [.md](https://openaitools.app/ko/tool/fal-ai.md) |
| 5 | [Together AI](https://openaitools.app/ko/tool/together-ai) | 1,645,930 | +64.9% | 무료+유료, 유료 | LLM 추론과 파인튜닝에 더 집중하지만, Replicate처럼 커뮤니티가 선별한 다양한 미디어 모델 카탈로그는 부족합니다. | [.md](https://openaitools.app/ko/tool/together-ai.md) |
| 6 | [KaneAI](https://openaitools.app/ko/tool/kaneai) | 901,340 | +13.2% | 무료+유료, 유료, 가격 문의 | 자연어로 계획·작성·자가 치유하는 생성형 AI 기반 E2E QA 에이전트 | [.md](https://openaitools.app/ko/tool/kaneai.md) |
| 7 | [Unsloth AI](https://openaitools.app/ko/tool/unsloth-ai) | 887,457 | -17.6% | 무료 | Specializes specifically in ultra-efficient model fine-tuning, rather than providing a general-purpose model hosting API. | [.md](https://openaitools.app/ko/tool/unsloth-ai.md) |
| 8 | [Atlas Cloud](https://openaitools.app/ko/tool/atlas-cloud) | 777,031 | -16.4% | 유료 | Offers a broad mix of generative media models via API, but lacks Replicate's massive community deployment ecosystem. | [.md](https://openaitools.app/ko/tool/atlas-cloud.md) |
| 9 | [Labelbox](https://openaitools.app/ko/tool/labelbox) | 762,803 | -22.8% | 가격 문의 | 최전선 AI가 학습하는 환경, 그리고 반복 업무를 맡는 에이전트 | [.md](https://openaitools.app/ko/tool/labelbox.md) |
| 10 | [Fireworks](https://openaitools.app/ko/tool/fireworks-ai) | 659,687 | +6% | 가격 문의 | 오픈 모델에 대해 뛰어나게 빠른 추론 속도를 제공하지만, Replicate보다 모델 선택 폭이 좁습니다. | [.md](https://openaitools.app/ko/tool/fireworks-ai.md) |

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출처: https://openaitools.app/ko/compare/foundry-vs-replicate-ai

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